<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>

COPY SCRIPT

For further information contact us at helpdesk@openaire.eu

Environmental Perception for Intelligent Vehicles

descriptionPublicationkeyboard_double_arrow_right Part of book or chapter of book 01 Jan 2018 Spain, United Kingdom Publisher:Elsevier BV

Authors: Armingol, Jose M.; Alfonso, Jorge; Aliane, Nourdine; Clavijo, Miguel; Campos-Cordobés, Sergio; de la Escalera, Arturo; del Ser, Javier; +10 Authors

doi: 10.1016/b978-0-12-812800-8.00002-3

handle: 11268/8099

Environmental Perception for Intelligent Vehicles

- Summary
- Subjects
- Metrics

Abstract

Environmental perception represents, because of its complexity, a challenge for Intelligent Transport Systems due to the great variety of situations and different elements that can happen in road environments and that must be faced by these systems. In connection with this, so far there are a variety of solutions as regards sensors and methods, so the results of precision, complexity, cost, or computational load obtained by these works are different. In this chapter some systems based on computer vision and laser techniques are presented. Fusion methods are also introduced in order to provide advanced and reliable perception systems.

Countries

Spain, United Kingdom

Related Organizations

Universidad Politécnica de Madrid
Spain
University of the Basque Country
Spain
Glasgow Caledonian University
United Kingdom
European University of Madrid
Spain

Keywords

Sistemas de asistencia a la conducción, environmental perception, Tecnología electrónica, intelligent vehicles, intelligent transportation systems, Vehículos de motor, ITS, Vehículo

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	7
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%