Survey of Bayesian Network applications to Intelligent Autonomous Vehicles (IAVs)

Díaz de León Torres, Rocío, Molina González, Martín ORCID: https://orcid.org/0000-0001-7145-1974 and Campoy Cervera, Pascual ORCID: https://orcid.org/0000-0002-9894-2009 (2019). Survey of Bayesian Network applications to Intelligent Autonomous Vehicles (IAVs). "eprint arXiv:1901.05517" ; pp. 1-34. ISSN 2331-8422.

Description

Title: Survey of Bayesian Network applications to Intelligent Autonomous Vehicles (IAVs)
Author/s:
Item Type: Article
Título de Revista/Publicación: eprint arXiv:1901.05517
Date: January 2019
ISSN: 2331-8422
Subjects:
Freetext Keywords: Bayesian Networks; Intelligent Autonomous Vehicles; Decision making
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

[thumbnail of INVE_MEM_2019_319715.pdf]
Preview
PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (298kB) | Preview

Abstract

This article reviews the applications of Bayesian Networks to Intelligent Autonomous Vehicles (IAV) from the decision making point of view, which represents the final step for fully Autonomous Vehicles (currently under discussion). Until now, when it comes making high level decisions for Autonomous Vehicles (AVs), humans have the last word. Based on the works cited in this article and analysis done here, the modules of a general decision making framework and its variables are inferred. Many efforts have been made in the labs showing Bayesian Networks as a promising computer model for decision making. Further research should go into the direction of testing Bayesian Network models in real situations. In addition to the applications, Bayesian Network fundamentals are introduced as elements to consider when developing IAVs with the potential of making high level judgement calls.

More information

Item ID: 64120
DC Identifier: https://oa.upm.es/64120/
OAI Identifier: oai:oa.upm.es:64120
Official URL: https://arxiv.org/ftp/arxiv/papers/1901/1901.05517...
Deposited by: Memoria Investigacion
Deposited on: 10 Nov 2020 11:40
Last Modified: 10 Nov 2020 11:40
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM