Towards Risk Estimation in Automated Vehicles Using Fuzzy Logic

Leonardo González; Enrique Martí; Isidro Calvo; Alejandra Ruiz; Joshue Pérez

doi:10.1007/978-3-319-99229-7_24

Towards Risk Estimation in Automated Vehicles Using Fuzzy Logic

Leonardo González
, Enrique Martí
, Isidro Calvo
, Alejandra Ruiz
, Joshue Pérez

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

9 Citas (Scopus)

14 Descargas (Pure)

Resumen

As vehicles get increasingly automated, they need to properly evaluate different situations and assess threats at run-time. In this scenario automated vehicles should be able to evaluate risks regarding a dynamic environment in order to take proper decisions and modulate their driving behavior accordingly. In order to avoid collisions, in this work we propose a risk estimator based on fuzzy logic which accounts for risk indicators regarding (1) the state of the driver, (2) the behavior of other vehicles and (3) the weather conditions. A scenario with two vehicles in a car-following situation was analyzed, where the main concern is to avoid rear-end collisions. The goal of the presented approach is to effectively estimate critical states and properly assess risk, based on the indicators chosen.

Idioma original	Inglés
Título de la publicación alojada	unknown
Editores	Friedemann Bitsch, Amund Skavhaug, Barbara Gallina, Erwin Schoitsch
Editorial	Springer Verlag
Páginas	278-289
Número de páginas	12
Volumen	11094
ISBN (versión digital)	978-3-319-99229-7
ISBN (versión impresa)	978-331999228-0, 9783319992280
DOI	https://doi.org/10.1007/978-3-319-99229-7_24
Estado	Publicada - 2018
Evento	Workshops: ASSURE, DECSoS, SASSUR, STRIVE, and WAISE 2018 co-located with 37th International Conference on Computer Safety, Reliability and Security, SAFECOMP 2018 - Västerås, Suecia Duración: 18 sept 2018 → 21 sept 2018

Serie de la publicación

Nombre	0302-9743

Conferencia

Conferencia	Workshops: ASSURE, DECSoS, SASSUR, STRIVE, and WAISE 2018 co-located with 37th International Conference on Computer Safety, Reliability and Security, SAFECOMP 2018
País/Territorio	Suecia
Ciudad	Västerås
Período	18/09/18 → 21/09/18

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

ODS 3: Salud y bienestar

Palabras clave

Automated vehicles
Collision avoidance
Fuzzy logic
Time-to-collision
Driving behavior

Project and Funding Information

Project ID
info:eu-repo/grantAgreement/EC/H2020/692474/EU/Architecture-driven, Multi-concern and Seamless Assurance and Certification of Cyber-Physical Systems/AMASS
Funding Info
This work was supported by the AMASS project (H2020-_x000D_ ECSEL) with grant agreement number 692474.

Acceder al documento

10.1007/978-3-319-99229-7_24

Paper 7Versión publicada final, 618 KB

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@inproceedings{250dedb812ae44e39f7ed2ea43409001,

title = "Towards Risk Estimation in Automated Vehicles Using Fuzzy Logic",

abstract = "As vehicles get increasingly automated, they need to properly evaluate different situations and assess threats at run-time. In this scenario automated vehicles should be able to evaluate risks regarding a dynamic environment in order to take proper decisions and modulate their driving behavior accordingly. In order to avoid collisions, in this work we propose a risk estimator based on fuzzy logic which accounts for risk indicators regarding (1) the state of the driver, (2) the behavior of other vehicles and (3) the weather conditions. A scenario with two vehicles in a car-following situation was analyzed, where the main concern is to avoid rear-end collisions. The goal of the presented approach is to effectively estimate critical states and properly assess risk, based on the indicators chosen.",

keywords = "Automated vehicles, Collision avoidance, Fuzzy logic, Time-to-collision, Driving behavior, Automated vehicles, Collision avoidance, Fuzzy logic, Time-to-collision, Driving behavior",

author = "Leonardo Gonz{\'a}lez and Enrique Mart{\'i} and Isidro Calvo and Alejandra Ruiz and Joshue P{\'e}rez",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2018.; Workshops: ASSURE, DECSoS, SASSUR, STRIVE, and WAISE 2018 co-located with 37th International Conference on Computer Safety, Reliability and Security, SAFECOMP 2018 ; Conference date: 18-09-2018 Through 21-09-2018",

year = "2018",

doi = "10.1007/978-3-319-99229-7\_24",

language = "English",

isbn = "978-331999228-0",

volume = "11094",

series = "0302-9743",

publisher = "Springer Verlag",

pages = "278--289",

editor = "Friedemann Bitsch and Amund Skavhaug and Barbara Gallina and Erwin Schoitsch",

booktitle = "unknown",

address = "Germany",

}

González, L, Martí, E, Calvo, I, Ruiz, A & Pérez, J 2018, Towards Risk Estimation in Automated Vehicles Using Fuzzy Logic. En F Bitsch, A Skavhaug, B Gallina & E Schoitsch (eds.), unknown. vol. 11094, 0302-9743, Springer Verlag, pp. 278-289, Workshops: ASSURE, DECSoS, SASSUR, STRIVE, and WAISE 2018 co-located with 37th International Conference on Computer Safety, Reliability and Security, SAFECOMP 2018, Västerås, Suecia, 18/09/18. https://doi.org/10.1007/978-3-319-99229-7_24

Towards Risk Estimation in Automated Vehicles Using Fuzzy Logic. / González, Leonardo; Martí, Enrique; Calvo, Isidro et al.
unknown. ed. / Friedemann Bitsch; Amund Skavhaug; Barbara Gallina; Erwin Schoitsch. Vol. 11094 Springer Verlag, 2018. p. 278-289 (0302-9743).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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AU - González, Leonardo

AU - Martí, Enrique

AU - Calvo, Isidro

AU - Ruiz, Alejandra

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N1 - Publisher Copyright: © Springer Nature Switzerland AG 2018.

PY - 2018

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N2 - As vehicles get increasingly automated, they need to properly evaluate different situations and assess threats at run-time. In this scenario automated vehicles should be able to evaluate risks regarding a dynamic environment in order to take proper decisions and modulate their driving behavior accordingly. In order to avoid collisions, in this work we propose a risk estimator based on fuzzy logic which accounts for risk indicators regarding (1) the state of the driver, (2) the behavior of other vehicles and (3) the weather conditions. A scenario with two vehicles in a car-following situation was analyzed, where the main concern is to avoid rear-end collisions. The goal of the presented approach is to effectively estimate critical states and properly assess risk, based on the indicators chosen.

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KW - Time-to-collision

KW - Driving behavior

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BT - unknown

A2 - Bitsch, Friedemann

A2 - Skavhaug, Amund

A2 - Gallina, Barbara

A2 - Schoitsch, Erwin

PB - Springer Verlag

T2 - Workshops: ASSURE, DECSoS, SASSUR, STRIVE, and WAISE 2018 co-located with 37th International Conference on Computer Safety, Reliability and Security, SAFECOMP 2018

Y2 - 18 September 2018 through 21 September 2018

ER -

Towards Risk Estimation in Automated Vehicles Using Fuzzy Logic

Resumen

Serie de la publicación

Conferencia

ODS de las Naciones Unidas

Palabras clave

Project and Funding Information

Acceder al documento

Otros archivos y enlaces

Huella

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