Environmental perception for intelligent vehicles

José M. Armingol; Jorge Alfonso; Nourdine Aliane; Miguel Clavijo; Sergio Campos-Cordobés; Arturo de la Escalera; Javier del Ser; Javier Fernández; Fernando García; Felipe Jiménez; Antonio M. López; Mario Mata; David Martín; José M. Menéndez; Javier Sánchez-Cubillo; David Vázquez; Gabriel Villalonga

doi:10.1016/B978-0-12-812800-8.00002-3

Environmental perception for intelligent vehicles

José M. Armingol, Jorge Alfonso, Nourdine Aliane, Miguel Clavijo, Sergio Campos-Cordobés, Arturo de la Escalera, Javier del Ser, Javier Fernández, Fernando García, Felipe Jiménez, Antonio M. López, Mario Mata, David Martín, José M. Menéndez, Javier Sánchez-Cubillo, David Vázquez, Gabriel Villalonga

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

7 Citations (Scopus)

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.

Original language	English
Title of host publication	Intelligent Vehicles
Subtitle of host publication	Enabling Technologies and Future Developments
Publisher	Elsevier
Pages	23-101
Number of pages	79
ISBN (Electronic)	9780128128008
ISBN (Print)	9780128131084
DOIs	https://doi.org/10.1016/B978-0-12-812800-8.00002-3
Publication status	Published - 1 Jan 2017

Keywords

Advanced driver assistance systems
Computer vision
Data fusion
Laser techniques
Traffic monitoring systemsvehicles

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/B978-0-12-812800-8.00002-3

Cite this

Armingol, J. M., Alfonso, J., Aliane, N., Clavijo, M., Campos-Cordobés, S., de la Escalera, A., del Ser, J., Fernández, J., García, F., Jiménez, F., López, A. M., Mata, M., Martín, D., Menéndez, J. M., Sánchez-Cubillo, J., Vázquez, D., & Villalonga, G. (2017). Environmental perception for intelligent vehicles. In Intelligent Vehicles: Enabling Technologies and Future Developments (pp. 23-101). Elsevier. https://doi.org/10.1016/B978-0-12-812800-8.00002-3

@inbook{3cc059b2db5b41bf8365acddc171a0c6,

title = "Environmental perception for intelligent vehicles",

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.",

keywords = "Advanced driver assistance systems, Computer vision, Data fusion, Laser techniques, Traffic monitoring systemsvehicles",

author = "Armingol, {Jos{\'e} M.} and Jorge Alfonso and Nourdine Aliane and Miguel Clavijo and Sergio Campos-Cordob{\'e}s and {de la Escalera}, Arturo and {del Ser}, Javier and Javier Fern{\'a}ndez and Fernando Garc{\'i}a and Felipe Jim{\'e}nez and L{\'o}pez, {Antonio M.} and Mario Mata and David Mart{\'i}n and Men{\'e}ndez, {Jos{\'e} M.} and Javier S{\'a}nchez-Cubillo and David V{\'a}zquez and Gabriel Villalonga",

year = "2017",

month = jan,

day = "1",

doi = "10.1016/B978-0-12-812800-8.00002-3",

language = "English",

isbn = "9780128131084",

pages = "23--101",

booktitle = "Intelligent Vehicles",

publisher = "Elsevier",

address = "Netherlands",

}

Armingol, JM, Alfonso, J, Aliane, N, Clavijo, M, Campos-Cordobés, S, de la Escalera, A, del Ser, J, Fernández, J, García, F, Jiménez, F, López, AM, Mata, M, Martín, D, Menéndez, JM, Sánchez-Cubillo, J, Vázquez, D & Villalonga, G 2017, Environmental perception for intelligent vehicles. in Intelligent Vehicles: Enabling Technologies and Future Developments. Elsevier, pp. 23-101. https://doi.org/10.1016/B978-0-12-812800-8.00002-3

TY - CHAP

T1 - Environmental perception for intelligent vehicles

AU - Armingol, José M.

AU - Alfonso, Jorge

AU - Aliane, Nourdine

AU - Clavijo, Miguel

AU - Campos-Cordobés, Sergio

AU - de la Escalera, Arturo

AU - del Ser, Javier

AU - Fernández, Javier

AU - García, Fernando

AU - Jiménez, Felipe

AU - López, Antonio M.

AU - Mata, Mario

AU - Martín, David

AU - Menéndez, José M.

AU - Sánchez-Cubillo, Javier

AU - Vázquez, David

AU - Villalonga, Gabriel

PY - 2017/1/1

Y1 - 2017/1/1

N2 - 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.

AB - 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.

KW - Advanced driver assistance systems

KW - Computer vision

KW - Data fusion

KW - Laser techniques

KW - Traffic monitoring systemsvehicles

UR - http://www.scopus.com/inward/record.url?scp=85081344184&partnerID=8YFLogxK

U2 - 10.1016/B978-0-12-812800-8.00002-3

DO - 10.1016/B978-0-12-812800-8.00002-3

M3 - Chapter

AN - SCOPUS:85081344184

SN - 9780128131084

SP - 23

EP - 101

BT - Intelligent Vehicles

PB - Elsevier

ER -

Environmental perception for intelligent vehicles

Abstract

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this