Navigational Freespace Detection for Autonomous Driving in Fixed Routes

Aparajit Narayan, Elio Tuci, William Sachiti, Aaron Parsons

Résultats de recherche: Contribution dans un livre/un catalogue/un rapport/dans les actes d'une conférenceArticle dans les actes d'une conférence/un colloque

1 Téléchargements (Pure)

Résumé

Vision-based modules are largely exploited by autonomous driving vehicles to identify the road area and to avoid collisions with other vehicles, pedestrians and obstacles. This paper illustrates the results of a comparative study in which eight different vision-based modules are evaluated for detecting free navigational space in urban environments. All modules are implemented using Convolutions Neural Networks. The distinctive and innovative feature of these modules is the manner via which navigational freespace is identified from image inputs. The modules generate the coordinates of a triangle, whose area represents the navigation freespace. The relative position of the triangle top corner with respect to the image centre points toward the vehicle direction of motion. Thus, when trained on a fixed route, these modules are able to successfully detect the road-freepsace and to make appropriate decisions concerning where to go at roundabouts, intersections etc., in order to reach the final destination.

langue originaleAnglais
titreESANN 2020 - Proceedings
Sous-titre28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
EditeurESANN (i6doc.com)
Pages715-720
Nombre de pages6
ISBN (Electronique)9782875870742
ISBN (imprimé)978-2-87587-073-5
Etat de la publicationPublié - 21 oct. 2020
Evénement28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2020 - Virtual, Online, Belgique
Durée: 2 oct. 20204 oct. 2020

Série de publications

NomESANN 2020 - Proceedings, 28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning

Une conférence

Une conférence28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2020
PaysBelgique
La villeVirtual, Online
période2/10/204/10/20

Empreinte digitale

Examiner les sujets de recherche de « Navigational Freespace Detection for Autonomous Driving in Fixed Routes ». Ensemble, ils forment une empreinte digitale unique.

Contient cette citation