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

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

9 Citations (Scopus)

14 Downloads (Pure)

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.

Original language	English
Title of host publication	unknown
Editors	Friedemann Bitsch, Amund Skavhaug, Barbara Gallina, Erwin Schoitsch
Publisher	Springer Verlag
Pages	278-289
Number of pages	12
Volume	11094
ISBN (Electronic)	978-3-319-99229-7
ISBN (Print)	978-331999228-0, 9783319992280
DOIs	https://doi.org/10.1007/978-3-319-99229-7_24
Publication status	Published - 2018
Event	Workshops: ASSURE, DECSoS, SASSUR, STRIVE, and WAISE 2018 co-located with 37th International Conference on Computer Safety, Reliability and Security, SAFECOMP 2018 - Västerås, Sweden Duration: 18 Sept 2018 → 21 Sept 2018

Publication series

Name	0302-9743

Conference

Conference	Workshops: ASSURE, DECSoS, SASSUR, STRIVE, and WAISE 2018 co-located with 37th International Conference on Computer Safety, Reliability and Security, SAFECOMP 2018
Country/Territory	Sweden
City	Västerås
Period	18/09/18 → 21/09/18

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

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.

Access to Document

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

Paper 7Final published version, 618 KB

Cite this

@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. in 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, Sweden, 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).

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

TY - GEN

T1 - Towards Risk Estimation in Automated Vehicles Using Fuzzy Logic

AU - González, Leonardo

AU - Martí, Enrique

AU - Calvo, Isidro

AU - Ruiz, Alejandra

AU - Pérez, Joshue

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

PY - 2018

Y1 - 2018

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.

AB - 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.

KW - Automated vehicles

KW - Collision avoidance

KW - Fuzzy logic

KW - Time-to-collision

KW - Driving behavior

KW - Automated vehicles

KW - Collision avoidance

KW - Fuzzy logic

KW - Time-to-collision

KW - Driving behavior

UR - https://www.scopus.com/pages/publications/85053938042

U2 - 10.1007/978-3-319-99229-7_24

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

M3 - Conference contribution

SN - 978-331999228-0

SN - 9783319992280

VL - 11094

T3 - 0302-9743

SP - 278

EP - 289

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

Abstract

Publication series

Conference

UN SDGs

Keywords

Project and Funding Information

Access to Document

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Cite this