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TAKEN: A Traffic Knowledge-Based Navigation System for Connected and Autonomous Vehicles.
Kamath B, Nikhil; Fernandes, Roshan; Rodrigues, Anisha P; Mahmud, Mufti; Vijaya, P; Gadekallu, Thippa Reddy; Kaiser, M Shamim.
Affiliation
  • Kamath B N; Department of Computer Science and Engineering, NMAM Institute of Technology, NITTE (Deemed to be University), Nitte 574110, India.
  • Fernandes R; Department of Computer Science and Engineering, NMAM Institute of Technology, NITTE (Deemed to be University), Nitte 574110, India.
  • Rodrigues AP; Department of Computer Science and Engineering, NMAM Institute of Technology, NITTE (Deemed to be University), Nitte 574110, India.
  • Mahmud M; Department of Computer Science, Computing and Informatics Research Centre, and Medical Technologies Innovation Facility, Nottingham Trent University, Clifton Lane, Nottingham NG11 8NS, UK.
  • Vijaya P; Department of Mathematics and CS, Modern College of Business and Science Bowshar, Muscat 133, Oman.
  • Gadekallu TR; Department of Information Technology Vellore Institute of Technology, Vellore 632014, India.
  • Kaiser MS; Department of Electrical and Computer Engineering, Lebanese American University, Byblos 13-5053, Lebanon.
Sensors (Basel) ; 23(2)2023 Jan 06.
Article in En | MEDLINE | ID: mdl-36679448
ABSTRACT
Connected and autonomous vehicles (CAVs) have witnessed significant attention from industries, and academia for research and developments towards the on-road realisation of the technology. State-of-the-art CAVs utilise existing navigation systems for mobility and travel path planning. However, reliable connectivity to navigation systems is not guaranteed, particularly in urban road traffic environments with high-rise buildings, nearby roads and multi-level flyovers. In this connection, this paper presents TAKEN-Traffic Knowledge-based Navigation for enabling CAVs in urban road traffic environments. A traffic analysis model is proposed for mining the sensor-oriented traffic data to generate a precise navigation path for the vehicle. A knowledge-sharing method is developed for collecting and generating new traffic knowledge from on-road vehicles. CAVs navigation is executed using the information enabled by traffic knowledge and analysis. The experimental performance evaluation results attest to the benefits of TAKEN in the precise navigation of CAVs in urban traffic environments.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Motor Vehicles / Autonomous Vehicles Language: En Journal: Sensors (Basel) Year: 2023 Document type: Article Affiliation country: India
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Motor Vehicles / Autonomous Vehicles Language: En Journal: Sensors (Basel) Year: 2023 Document type: Article Affiliation country: India