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A Review of Sensor Technologies for Perception in Automated Driving

  • Enrique David Marti
  • , Miguel Angel de Miguel
  • , Fernando Garcia
  • , Joshue Perez

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

297 Citas (Scopus)
218 Descargas (Pure)

Resumen

After more than 20 years of research, ADAS are common in modern vehicles available in the market. Automated Driving systems, still in research phase and limited in their capabilities, are starting early commercial tests in public roads. These systems rely on the information provided by on-board sensors, which allow to describe the state of the vehicle, its environment and other actors. Selection and arrangement of sensors represent a key factor in the design of the system. This survey reviews existing, novel and upcoming sensor technologies, applied to common perception tasks for ADAS and Automated Driving. They are put in context making a historical review of the most relevant demonstrations on Automated Driving, focused on their sensing setup. Finally, the article presents a snapshot of the future challenges for sensing technologies and perception, finishing with an overview of the commercial initiatives and manufacturers alliances that will show future market trends in sensors technologies for Automated Vehicles.
Idioma originalInglés
Número de artículo8846569
Páginas (desde-hasta)94-108
Número de páginas1
PublicaciónIEEE Intelligent Transportation Systems Magazine
Volumen11
N.º4
DOI
EstadoPublicada - 23 sept 2019

Palabras clave

  • Automated Driving
  • Cameras
  • Robot sensing systems
  • Accidents
  • Laser radar
  • Roads

Project and Funding Information

  • Project ID
  • info:eu-repo/grantAgreement/EC/H2020/692455/EU/European Initiative to Enable Validation for Highly Automated Safe and Secure Systems/ENABLE-S3
  • Funding Info
  • This work has been partly supported by ECSEL Project ENABLE-_x000D_ S3 (with grant agreement number 692455-2), by the_x000D_ Spanish Government through CICYT projects (TRA2015-_x000D_ 63708-R and TRA2016-78886-C3-1-R).

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