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Towards multi-camera system for the evaluation of motorcycle driving test

Contributo in Atti di convegno
Data di Pubblicazione:
2022
Abstract:
This work describes the early stage of an interactive and accelerated AI-driven framework for Practical Driving Courses and Driving Licence Exams. The core of the project is an innovative multi-parameter AI-assisted telemetry system able to compute test scores and outcome, useful for human-neutral auditability of Driving Licence Exams. The distributed Artificial Intelligence (AI) system available at the Track Testbed will be able to perform driving behaviour classifications and will suggest specific improvements based on the analysis of vehicle trajectories acquired during the driving test. Finally, the project will target the creation of a large dataset for driving test classification of key performance parameters. The system is envisioned to have a relevant impact on all the certification, driving licence operators and regulator entities.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
Camera-base systems; Edge computing; Trajectory analysis; Computer vision; Artificial intelligence; Motorcycle driving test
Elenco autori:
Moroni, Davide; Righi, Marco; Leone, GIUSEPPE RICCARDO
Autori di Ateneo:
LEONE GIUSEPPE RICCARDO
MORONI DAVIDE
RIGHI MARCO
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/415405
Link al Full Text:
https://iris.cnr.it//retrieve/handle/20.500.14243/415405/163485/prod_471275-doc_191343.pdf
  • Dati Generali

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URL

https://ieeexplore.ieee.org/document/10090154
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